Unconventional well gas to oil ratio characterization

ABSTRACT

A method of reducing gas flaring through modelling of reservoir behavior using a method of optimizing oil production from one or more well(s) in a reservoir, the method providing a model of the well, inputting well data for a one or more well(s) into the model, the well data selected from geological layers, reservoir properties, fracturing data, completion data, permeability data, geochemistry, and combinations thereof. Inputting historical production data from one or more well(s) into the model, the historical data selected from PVT data, BHP, oil production rates, gas production rates and water production rates, or combinations thereof. Controlling the model to match one or more parameters selected from production rates, gas to oil ratio (GOR), bottom hole pressure (BHP), cumulative oil production (COP), or a combination thereof in a probabilistic manner to obtain a plurality of historical models. Verifying one or more test models against the historical models to identify an optimal model with minimum error. Using the optimal model to predict one or more parameters selected from production rates, gas to oil ratio (GOR), bottom hole pressure (BHP), cumulative oil production (COP), or a combination thereof from the well into a future. Optimizing a production plan using the predicted parameters and implementing the optimized production plan in said well, whereby oil production is optimized as compared to a similar well produced without the optimized production plan.

PRIOR RELATED APPLICATIONS

This application claims priority to 63/196,648, filed Jun. 3, 2021, andincorporated by reference in its entirety for all purposes.

FEDERALLY SPONSORED RESEARCH STATEMENT

Not applicable.

FIELD OF THE DISCLOSURE

The disclosed methods relate generally to the optimization of areservoir production, in particular gas to oil levels.

BACKGROUND OF THE DISCLOSURE

With technically recoverable reserves estimated by United StatesGeological Survey (USGS) to be between 4.4 and 11.4 billion barrels,Bakken is one of the earliest hybrid unconventional plays to bedeveloped into a mature asset by the industry. The Williston Basincontains a complete stratigraphic record from the Cambrian to Tertiarywith sediment thickness of over 16,000 feet with multiple conventionaland unconventional targets that have been exploited over the last 40years.

The Bakken Formation within the Williston Basin has three main reservoirtargets and two potential source rocks (FIG. 1A-B): the Upper BakkenShale and the Lower Bakken Shale source rocks were deposited in asub-oxic to anoxic offshore marine depositional environment with astratified water column, whereas the Middle Bakken (MB) member wasdeposited in a marine to marginal setting under oxic conditions. Theunits of the Three Fork members like the Upper Three Forks (UTF) and theMiddle Three Forks (MTF) are mainly cyclical deposits of wind-blownsilts deposited in shallow wet lacustrine environment that areinterbedded with green silty dolomitic claystones.

The Williston basin and the Bakken formation horizontal developmentstarted in the early 2000's and ramped up into the latter part of thedecade. Many of these wells were drilled in single well drilling spaceunits (DSUs) with smaller intensity, sleeve completion designs. The mostcommon artificial lift (AL) used early on was rod pump. As field oilproduction ramped up in 2015, the associated gas also peaked, but thegas to oil ratio (GOR) was relatively stable or slowly increasing. SeeFIG. 2 .

As more development and investment was made in 2017/2018, we also sawmore intense completion designs, tighter well spacing, AL optimization,and depletion effects with it. As the oil peaked again in 2019, thistime the fieldwide GOR was much higher and with that came record highgas production. Many operators and gas gatherers capacity wereoverwhelmed, and higher flaring was seen throughout the field. This inconjunction with the higher attention on the environment created agreater focus and collaboration in Bakken to handle the gas. As moreofftake capacity was created, operators also came forward withinnovative solutions and uses for the excess gas.

We continue to see ever increasing GOR and gas rates throughout thefield, highlighting the importance of accurate forecasting andprediction of GOR. The proper forecasting will allow us to maximizeproduction, increase economics, and do so in an environmentally friendlymanner. This invention addresses one or more of these needs.

SUMMARY OF THE DISCLOSURE

With the increased focus on the environment, the oil and gas industry istaking aggressive action to reduce greenhouse gas (GHG) and flareemissions. As an important part, characterizing the GOR fromUnconventional Resources (UR) wells will help predict long-term gasproduction trends and develop high GOR mitigation strategies. In thisdisclosure, the short- and intermediate-term GOR behaviors are discussedbased on Bakken wells with different completion designs and the keydrivers and mechanisms dictating the GOR trends are investigated. Anovel modeling workflow is developed to match GOR & other observed dataand forecast long-term GOR trends. Potential techniques to mitigaterising GOR are also proposed.

The GOR data from a large number of wells were analyzed to identify GORcorrelations with fluid properties, completion design, depletion,drawdown strategy and artificial lift. Multiple types of data werecollected in this study in conjunction with production data, includinglong-term bottom hole pressure (BHP), pressure volume, temperature data(PVT), interference test and shut-in data. Data driven reservoir modelswere built to match the GOR behaviors for both old sliding sleevecompletion wells and modern plug-and-perf completion wells. Long-termGOR trends were predicted with the calibrated reservoir model.

The key insights and conclusions from this work included: 1) Bakkenunconventional GOR shows conventional black oil reservoir GOR behaviors,but it also has many unconventional characteristics due to the lowmatrix permeability and different types of hydraulic fracture systemscreated. 2) GOR trends are sensitive to pressure drawdown. Strongcorrelations between GOR and BHP are observed. 3) Old sliding sleevecompletion well GOR shows cyclical rise-and-fall patterns with agradually increasing long-term trend, whereas modern completion wellsshow rising GOR trend after their BHPs drop below bubble point pressure(P_(b)) and then reach an intermediate-term plateau. 4) Offset parentwell depletion drives child well GOR to rise faster and to a higherlevel. 5) Less aggressive drawdown, recharging due to frac hits and longshut-in can delay/mitigate GOR rising. Finally, 6) Bakken well GORbehaviors can be accurately modeled using the proposed approach.

The learnings presented herein improve our understanding ofunconventional well GOR trends in the industry. Better GORcharacterization will improve forecasting for offtake capacity and flareemission reduction and help the industry to meet environmentalstandards. The analysis and modeling approaches proposed herein can alsospark further research and development activities.

Although GOR is specifically exemplified herein, the method is not solimited and can be used to optimize other well parameters, as desired bythe operator.

The present methods include any of the following embodiments in anycombination(s) of one or more thereof:

A method of optimizing oil production from a well in a reservoir, saidmethod comprising:  a) providing a model of said well;  b) inputtingwell data for a plurality of wells into said model, said well dataselected from geological layers, reservoir properties, fracturing data,completion data, permeability data, geochemistry, and combinationsthereof;  c) inputting historical production data from said plurality ofwells into said model, said historical data selected from PVT data, BHP,oil production rates, gas production rates and water production rates,or combinations thereof;  d) controlling said model to match one or moreparameters selected from production rates, gas to oil ratio (GOR),bottom hole pressure (BHP), cumulative oil production (COP), or acombination thereof in a probabilistic manner to obtain a plurality ofhistorical models;  e) verifying one or more test models against saidhistorical models to identify an optimal model with minimum error;  f)using said optimal model to predict one or more parameters selected fromproduction rates, gas to oil ratio (GOR), bottom hole pressure (BHP),cumulative oil production (COP), or a combination thereof from said wellinto a future;  g) optimizing a production plan using said predictedparameters;  h) implementing said optimized production plan in saidwell, whereby oil production is optimized as compared to similar wellproduced without said optimized production plan. A method of reducingGOR in oil production from one or more well(s) in a reservoir, saidmethod comprising:  a) providing a model of said one or more well(s); b) inputting well data from one or more well(s) into said model, saidwell data selected from geological layers, reservoir properties,fracturing data, completion data, permeability data, geochemistry, andcombinations thereof;  c) inputting historical production data from saidone or more well(s) into said model, said historical data selected fromPVT data, BHP, oil production rates, gas production rates and waterproduction rates, and combinations thereof;  d) controlling said modelto match one or more parameters selected from production rates, gas tooil ratio (GOR), bottom hole pressure (BHP), cumulative oil production(COP), or a combination thereof in a probabilistic manner to obtain aplurality of historical models;  e) verifying one or more test modelsagainst said historical models to identify an optimal model with minimumerror;  f) using said optimal model to predict gas to oil ratio (GOR)from said one or more well(s) into a future;  g) optimizing a productionplan using said predicted GOR to reduce gas production;  h) implementingsaid optimized production plan in said well, whereby GOR is reduced ascompared to said predicted GOR. Any method herein described, whereinsaid reservoir is an unconventional reservoir. Any method hereindescribed, wherein said reservoir is a hybrid shale and limestonereservoir. Any method herein described, wherein said model in a) hasfiner gridding near said well. Any method herein described, wherein saidfiner gridding is Tartan gridding. Any method herein described, whereinsaid optimized reservoir plan includes reduced drawdown to reduce GOR.Any method herein described, wherein said optimized reservoir planincludes widening fracture cluster spacing to reduce GOR. Any methodherein described, wherein said optimized reservoir plan includesrecharging high GOR parent wells with offset child well fracture hits toreduce GOR. Any method herein described, wherein said optimizedreservoir plan includes extending well shut-in to reduce GOR.

As used herein, a regular grid is a network of crossing right anglelines, such as is seen on graph paper. In reservoir modelling, grids maybe two dimensional and need not be at right angles or regular. A commonrequirement in reservoir simulation is an increased level of detailaround an item of interest such as a well. A “tartan” grid has variableheight and/or width of the lines and is a gridding style available insome reservoir modelling programs.

As used herein, a “reservoir” is a formation or a portion of a formationthat includes sufficient permeability and porosity to hold and transmitfluids, such as hydrocarbons or water or natural gas, and the like.

A reservoir can have a plurality of chemically distinct “zones” therein,particularly in very tight rock, where mixing is almost non-existent.The data herein can be catalogued by zone, allowing that portion of thedata to be used for other zones, even in other wells, as long as thezone has similar fingerprints.

A “production plan” can include placement of wells, length of well,depth of well, completion details, enhanced oil production methods,stimulation methods, fracking methods, order of completion, productionrate, and the like. Production plans can also include well stacking,well spacing, completion designs (frac job types, job size, number ofstages, number of clusters per stage, etc.) and strategies (e.g., atwhat sequence to frac different target zones, how tosynchronize/coordinate with nearby wells, alternating or zipperfracking, etc.), production well pressure management, enhanced oilrecovery strategies, and the like.

An “optimized” production plan is generated using well predictions andmodeling to improve the simulated production from a well. Once a wellplan is optimized, it may then be implemented at the well, at a well padwith multiple wells, or in an area penetrating one or more reservoirsand used to produce hydrocarbons or other reservoir fluids.

To “implement” an optimized plan means to actually drill and/or completea well or wells according to the plan and then produce hydrocarbons fromthat well.

Reservoir performance during primary depletion is controlled largely bythe natural drive mechanisms present. bOnce the drive mechanisms areknown, material balance methods may be used to analyze and predictreservoir performance. Drive mechanisms are the natural sources ofreservoir energy which cause oil and gas to flow into a wellbore. Thethree primary reservoir drive mechanisms are solution gas drive, gas capdrive, and water drive. Gravity drainage is a secondary drive mechanismcapable of improving recovery in steeply dipping or high permeabilityreservoirs. The active drive mechanisms can often be identified from areservoir's gas/oil ratio, reservoir pressure, and production ratehistories. Early identification of the active drive mechanisms may beimportant to optimize a reservoir's performance.

As used herein, “cumulative oil” or “Cumulative Oil Produced” (COP) isthe total amount of oil produced over time.

As used herein, “cumulative gas” is the total amount of gas producedover time.

As used herein, “water cut” is the ratio of water produced compared tothe volume of total liquids produced.

As used herein, “production rate” is the rate of fluid production fromthe well. Production rates can be adjusted by changing the amount offluid produced and are dependent upon the reservoirs rate of inflow andbottom hole pressure. Inflow performance relationship is controlled bythe ratio of bottom hole pressure to production rate.

As used herein, “Gas Oil Ratio” or “GOR” is the volume of gas that isproduced from crude oil when the oil is being extracted from thereservoir to the earth's surface through production tubing. This isgenerally related to associated gas or saturated gas in the oilreservoir. It is represented as standard cubic feet per stock tankbarrel (scf/stb).

The “associated gas” is natural gas that is dissolved in the oil and isproduced along with the crude oil. Heavy crude oil has low API gravityand low capacities of dissolved gas as compared to lighter crude oil.

“Steam to Oil Ratio” or “SOR” is a measure used to quantify theefficiency of production of oil from a reservoir based on steaminjection into the reservoir. It can be defined as the amount of steaminjected to produce one unit volume of crude oil. The steam isquantified by barrels of water used to make the steam, however. Forexample, a steam-oil ratio is 4.5 means that 4.5 barrels ofwater—converted into steam and injected into the well—were required toextract a single barrel of oil.

“API gravity” measures the relative density of petroleum liquid andwater and has no dimensions. To derive the API gravity, the specificgravity (SG) is first measured using either the hydrometer, detailed inASTM D1298 or with the oscillating U-tube method detailed in ASTM D4052.The official formula used to derive the gravity of petroleum liquidsfrom the specific gravity (SG), as follows: API gravity=141.5/SG−131.5.

A “core” or “rock core” is a sample of rock, typically in the shape of acylinder. Taken from the side of a drilled oil or gas well, a core isthen dissected into multiple core plugs, or small cylindrical samplesmeasuring about 1 inch in diameter and 3 inches long.

“Drilling cuttings” or “cutting samples” are the small irregular rocksamples generated during drilling and returned with the drilling mud.

As used herein, the term “fracture hit” was initially coined to refer tothe phenomenon of an infill-well fracture interacting with an adjacentwell during the hydraulic-fracturing process. However, over time, itsuse has been extended to any type of well interference or interaction inunconventional reservoirs.

By “obtaining” a sample herein we do not necessarily implycontemporaneous sampling procedures because existing samples can be usedwhere available. However, often contemporaneous sample collection willbe needed, except for core or cutting samples, which may already beavailable.

By generating a reservoir “map” we mean that the reservoir ischaracterized in the three directional axes as well as the fourth timeaxis, but we do not necessarily imply a graphical representationthereof, as data can be maintained and accessed in many forms, includingin tables. The map may be segmented into zones, where the fingerprintingdata is very similar.

The use of the word “a” or “an” when used in conjunction with the term“comprising” in the claims or the specification means one or more thanone, unless the context dictates otherwise.

The term “about” means the stated value plus or minus the margin oferror of measurement or plus or minus 10% if no method of measurement isindicated.

The use of the term “or” in the claims is used to mean “and/or” unlessexplicitly indicated to refer to alternatives only or if thealternatives are mutually exclusive.

The terms “comprise”, “have”, “include” and “contain” (and theirvariants) are open-ended linking verbs and allow the addition of otherelements when used in a claim.

The phrase “consisting of” is closed, and excludes all additionalelements.

The phrase “consisting essentially of” excludes additional materialelements, but allows the inclusions of non-material elements that do notsubstantially change the nature of the invention. Any claim or claimelement introduced with the open transition term “comprising,” may alsobe narrowed to use the phrases “consisting essentially of” or“consisting of,” and vice versa. However, the entirety of claim languageis not repeated verbatim in the interest of brevity herein.

The following abbreviations may be used herein:

ABBREVIATION TERM AL ARTIFICIAL LIFT API AMERICAN PETROLEUM INSTITUTE,ALSO API GRAVITY, IS A MEASURE OF HOW HEAVY OR LIGHT A PETROLEUM LIQUIDIS COMPARED TO WATER: IF ITS API GRAVITY IS GREATER THAN 10, IT ISLIGHTER AND FLOATS ON WATER; IF LESS THAN 10, IT IS HEAVIER AND SINKS.ASTM AMERICAN SOCIETY FOR TESTING AND MATERIALS BBL BARREL BHPBOTTOMHOLE PRESSURE, PSIA BVO BULK VOLUME OIL CPU CENTRAL PROCESSINGUNIT CGR CONDENSATE GAS RATIO-CGR GIVES A MEASURE OF THE LIQUID CONTENTTO THE VOLUME OF GAS. IT IS MEASURED IN BARRELS PER MILLIONS OF STANDARDCUBIC FEET (BARRELS/MMSCF). COP CUMULATIVE OIL PRODUCTION CUM CUMULATIVEDRV DRAINED ROCK VOLUMES DSU DRILLING SPACING UNIT EOS EQUATIONS OFSTATE ESP ELECTRICAL SUBMERSIBLE PUMP GHG GREENHOUSE GAS GOR GAS TO OILRATIO-WHEN OIL IS PRODUCED TO SURFACE TEMPERATURE AND PRESSURE IT ISUSUAL FOR SOME NATURAL GAS TO COME OUT OF SOLUTION. THE GAS/OIL RATIO(GOR) IS THE RATIO OF THE VOLUME OF GAS THAT COMES OUT OF SOLUTION TOTHE VOLUME OF OIL AT STANDARD CONDITIONS (TEMPERATURE = 273.15 K,PRESSURE = 1 BAR) GPU GRAPHICS PROCESSING UNIT GUI GRAPHICAL USERINTERFACE LB POUNDS LBS LOWER BAKKEN SHALE MB MIDDLE BAKKEN MBO THOUSANDBARREL OF CRUDE OIL MTF MIDDLE THREE FORKS NDIC NORTH DAKOTA INDUSTRIALCOMMISSION P_(B) BUBBLE POINT PRESSURE, PSIA P_(I) INITIAL RESERVOIRPRESSURE, PSIA PV PRESSURE VOLUME PVT PRESSURE VOLUME TEMPERATURE P_(WF)FLOWING BOTTOM HOLE PRESSURE, PSIA RAM RANDOM ACCESS MEMORY ROMREAD-ONLY MEMORY R_(SI) INITIAL SOLUTION GOR, SCF/STB SCF STANDARD CUBICFOOT S_(G) GAS SATURATION, FRACTION S_(GC) CRITICAL GAS SATURATION,FRACTION SOR STEAM TO OIL RATIO SRV STIMULATED ROCK VOLUMES TLG TIMELAPSE GEOCHEMISTRY-GEOCHEMICAL FINGERPRINTS TAKEN FROM A PLURALITY OFSAMPLES COLLECTED OVER TIME UBS UPPER BAKKEN SHALE UR UNCONVENTIONALRESOURCES USGS US GEOLOGICAL SURVEY UTF UPPER THREE FORKS

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A. Map showing the study area around Nesson anticline.

FIG. 1B Main reservoir formations in the Bakken.

FIG. 2 . Historical Bakken oil, gas and flaring rates from NDIC.

FIG. 3 . Old completion well GOR trends as a function of oil rate anddownhole measured BHP (1st year data).

FIG. 4 . Old completion well longer term GOR trends as a function of oilrate and downhole measured BHP (˜5-year data).

FIG. 5 . Modern completion well GOR trends as a function of oil rate anddownhole measured BHP.

FIG. 6A. GOR trends by fluid property areas.

FIG. 6B. GOR rising magnitude by fluid property areas.

FIG. 7 . Comparison of GOR for 2 wells on gas lift versus rod pump.

FIG. 8A. GOR rising magnitude vs. production months comparison betweenparent and child wells.

FIG. 8B. GOR rising magnitude vs. cumulative oil production comparisonbetween parent and child wells.

FIG. 9A. schematic of parent vs. child well placement.

FIG. 9B. Impact of child well fracture hits on parent well GOR and oilrate uplift, tubing pressure and GOR pre- and post-fracture vs. time.

FIG. 10A. GOR rising magnitude vs. oil production rate.

FIG. 10B. GOR rising magnitude vs. gas production rate.

FIG. 11A. Bi-wing hydraulic fractures used in reservoir model for GORstudy.

FIG. 11B. Grid refinement near fractures and wells used in reservoirmodel for GOR study.

FIG. 12A. Production history matching BHP for old completion wells.

FIG. 12B. Production history matching cumulative oil for old completionwells.

FIG. 12C. Production history matching GOR for old completion wells.

FIG. 13 . Reservoir pressure and gas saturation evaluation at differentGOR stages of old completion wells; where BHP>P_(b), where BHP dropsbelow P_(b), Early Pressure build-up, Later Pressure build-up, and laterflowing.

FIG. 14A. Production history matching of BHP for modern completionwells.

FIG. 14B. Production history matching of cumulative oil for moderncompletion wells.

FIG. 14C. Production history matching of GOR for modern completionwells.

FIG. 15 . Reservoir pressure and gas saturation evaluation at differentGOR stages of modern completion wells; where P_(wf)>P_(b), where P_(wf)just dropped below P_(b), and where GOR enters a plateau stage.

FIG. 16A. Old completion well forecasts of BHP.

FIG. 16B. Old completion well forecasts of GOR.

FIG. 17A. Modern completion well forecasts of BHP.

FIG. 17B. Modern completion well forecasts of GOR (short term).

FIG. 17C. Modern completion well forecasts of GOR (long term).

FIG. 17D. Modern completion well forecasts with less aggressive drawdownBHP.

FIG. 17E. Modern completion well forecasts with less aggressive drawdownGOR (short term).

FIG. 17F. Modern completion well forecasts of less aggressive drawdownGOR (long term).

FIG. 18A. Impacts of cluster spacing on BHP vs. time.

FIG. 18B. Impacts of cluster spacing on GOR vs. time.

FIG. 18C. Impacts of cluster spacing on cumulative (CUM) oil vs. time.

FIG. 18D showing tight cluster spacing (solid lines in FIG. 18A-C).

FIG. 18E showing wider cluster spacing (starred lines in FIG. 18A-C).

DETAILED DESCRIPTION OF THE DISCLOSURE

Herein, we present our findings on Bakken GOR trends based onhigh-quality data collected, integrated modeling and the analysis ofhundreds of wells in the area.

Unlike Permian and Eagle Ford, Bakken is a hybrid play of shale andcarbonate. The reservoir matrix permeability is at the low single-digitmicro-Darcy range. It is about one order of magnitude higher than othershale plays, however it is still much lower than conventional reservoirpermeability. This has important implications on the Bakken reservoirdepletion process and GOR evolution that will be discussed later.

Bakken reservoir fluids generally fall in black oil to volatile oilfluid regimes with a wide range of initial solution GOR R_(si) from 500to 2500 scf/stb in the study area. The initial reservoir pressure P_(i)varies from 6500 to 7500 psi. Many PVT samples were collected and testedacross the field to characterize fluid properties. A field wideEquations of State (EOS) model was developed for various applications,including GOR modeling and facility design.

Completion design is a key driver of Bakken well GOR behaviors. We willuse two main completion design types (old completion and new completion)to illustrate the typical GOR stages and trends in the short andintermediate-terms in our proof of concept demonstrations. Most of thewells drilled before 2016 have old completion designs—open hole slidingsleeve, few stages (30 or less) and low proppant volume (5 million lbsor less). Modern completion designs normally are associated withcemented plug-and-perf completions, more stages (30+) and larger frackjob sizes (8+ million lbs proppant).

GOR Trends for Old Completion Design Wells

The old completion wells were developed when reservoir pressure wasclose to original virgin pressure P_(i), i.e., there was no parent welldepletion impact. Their stimulated rock volumes (SRV) were small withfewer long fractures, which can lead to faster drawdown and lower wellproductivity. These created unique GOR characteristics for this type ofwells. Examples are given in FIG. 3 and FIG. 4 , where oil rate, GOR anddownhole gauge BHP pressure data are overlayed. The main observationsare:

1) GOR started flat with GOR=R_(si), while well flowing bottom holepressure (P_(wf)) was above bubble point pressure (P_(b)=˜3000 psi), asshown in FIG. 3 ;

2) GOR rose while P_(wf) dropped below P_(b) (arrow 1);

3) GOR trended downward (arrow 1) when P_(wf) reached a temporary lowlimit due to rod pump production constraints in this case;

4) Post the operational shut-ins (e.g. downhole isolation for offsetfracking), GOR came down to R_(si) (arrow 3). It rose back up asproduction resumed and P_(wf) dropped further (arrow 4). The mechanismand theory will be discussed in the modeling section.

The GOR rise-and-fall cycle repeated itself throughout the short tointermediate-term of the well production (FIG. 3 ). However, in eachsubsequent cycle, the P_(wf) built up to a lower pressure and GOR roseto a higher level though the rising pace was slow. This GORrise-and-fall pattern is commonly observed among Bakken old-stylecompletion wells.

A very strong correlation between producing GOR and BHP was observedfrom this data. GOR is much more sensitive to P_(wf) changes inunconventional reservoirs than in conventional reservoirs thanks to URlow matrix permeability and limited drained rock volume (DRV).

It is also interesting to see that P_(wf) gradually increased while thewell was on production, as indicated by arrow 2 in FIG. 4 . This couldbe caused by rod pump curtailed production and relatively fasterpressure recovery from areas surrounding fractures, given the highermatrix permeability in the Bakken as compared against other shale plays.It is also consistent with early discussions that GOR moved downwardduring the P_(wf) rising period. This observation underscores theimportance of collecting long-term downhole BHP data to understand GORand reservoir depletion.

The flat GOR period was short, only 2 months in this example. Theduration of the flat GOR is dictated by the pressure difference betweenP_(i) and P_(b), and the pressure drawdown, which is a function of welloperating practices and stimulated hydraulic fracture system supportingthe well deliverability.

GOR Trends for Modern Completion Design Wells

Modern completion wells show different GOR trends from old completionwells. An example is given in FIG. 5 , where oil rates, GOR and downholegauge BHP pressure data are overlayed. The main observations are givenbelow:

1) The flat GOR period lasted longer (5+ months). The modern completiondesigns created much larger SRV/DRV and resulted in higher wellproductivity, which can keep p_(wf) above p_(b) for a longer time.

2) GOR started rising as P_(wf) dropped below P_(b), but a moderncompletion well GOR rises slower than an old completion well in theearly time as compared to later (Arrow 1 v. 2). The rising periods canlast from several months to over a year in Bakken.

3) GOR reached a plateau as P_(wf) further decreased in the intermediateterm. The plateau had not been well established in this particular case.

It is also worth mentioning that Bakken GOR data do not show strongcritical gas saturation (S_(gc)) behavior, i.e., GOR does not show aclear dip right before it starts rising. Our interpretation is becausethe drainage areas are very limited prior to gas breakout, it does nottake a large amount of free gas to make the drained areas reach S_(gc).This may create a short GOR dipping period (if there is one), which canbe easily masked by the producing GOR fluctuations.

Building on the GOR stages identified in the previous sections, we alsoinvestigated other GOR trend drivers based on hundreds of Bakken wells'production data with the focus on modern completion wells in the studyarea.

Fluid Property Spatial Variation

The fluid property spatial variations can have significant impacts onGOR. In this study area, the south part has lower R_(si) and P_(b), andthe oil is less volatile than that in the north side. Four similar PVTproperty areas are defined—Areas 1, 2, 3 and 4 from south to north. Thefirst 25-month average well GOR of each area is shown in FIG. 6A. TheGOR rising magnitude, defined as normalized GOR by initial solution GOR(GOR/R_(si)) is shown in FIG. 6B. As the oil becomes increasingly morevolatile from south areas to north areas, the initial solution GORR_(si) moves higher and the producing GOR rises to a higher plateau at afaster pace.

Well Operating Strategy/Drawdown

As mentioned earlier, one of the biggest drivers in well GOR is thedrawdown of the well and thus the lower P_(wf). Many of the earlierwells were lifted with rod pumps after the flowing period. Often theinstallation of a rod pump early in the life of the well will constrainthe amount of the fluid it will produce. A fluid column will then formin the well, keeping some back pressure on the formation and higherP_(wf) These wells would then stay above P_(b) longer and with lessaggressive drawdown would not see the GOR rise as quickly.

Comparatively, the industry has switched to more electrical submersiblepumps (ESPs) and gas lift design early on in the well life. Both arecapable of handling more fluid, and in turn drawing the bottom holepressure down lower. This more aggressive drawdown will cause more rockvolume to drop below P_(b) and faster. The GOR is then seen to rise moreearly on and reach higher peak GORs than rod pump wells with similarcompletion designs.

Error! Reference source not found. compares 2 well's GORs on the samepad with the same formation, completion design, and timing. Both wellsflowed until around October 2018 with identical GORs. After that time,one well was put on gas lift and the other on rod pump. One can see theGOR differences post AL installation with the gas lift well GOR risingmuch faster and higher than the other. This proves the value of reducingdrawdown rates.

Offset Parent Well Depletion

As an unconventional field is developed into a mature asset, the parent(existing wells) and child (offset new wells) situation becomes more andmore common, and it can have important impacts on new development wellGOR. Inevitably, child wells will start production at a lower pressurethan the original P_(i) due to the parent well depletion. This leavessmaller room for the child well's P_(wf) to drop before it reachesP_(b). FIG. 8A compares the GOR trends between parent wells and childwells. The flat GOR period of child well is much shorter than that ofparent wells. In addition, child well GOR rises to a higher plateau.FIG. 8B plots the GOR rising magnitude against cumulative oil volumeinstead of production months. We can draw the similar conclusion—thechild well cumulative oil production is lower before the start of risingGOR.

Fracture Hits

Fracture hits (cross-well communication created by hydraulic fracturing)on parent wells are created by offset well fracturing. A parent-childwell schematic is given in FIG. 9A. Since the stress and pressure nearparent well areas are lower due to depletion, child hydraulic fracturestend to asymmetrically grow towards parent wells and generate strongfracture hits, as indicated by the tubing pressure jump post fracturehits in FIG. 9B. In the Bakken, the parent well production normallybenefits from fracture hits. See the oil rate uplift post fracture hitsin FIG. 9B. Also, it is worth noting that the rising GOR prior tofracture hits is suppressed to a much lower level for a long periodtime. Possible reasons include re-pressurization of the parent wellprevents more areas dropping below P_(b), or fracture hits create newfractures near parent wells that contact new higher-pressure rockvolumes.

Well Oil and Gas Production Rates

Bakken well oil production rates normally begin with a plateau in theearly time, given the higher reservoir pressure and facilityconstraints. It is also common that a well's oil rate plateau endcoincides with the beginning of the GOR rise. The oil rate can showfaster decline with rising GOR because the high gas mobility enables gasto move preferentially to oil from the reservoir to the wellbore. SeeFIG. 5 and FIG. 10A-B. Statistically, Bakken data show the GOR risinghappens when oil rates drop from 700 stb/day to 300 stb/day (FIG. 10A).However, the gas production rates are relatively stable in the short-and intermediate-terms, i.e., the declining oil rate and rising GOR makethe gas rate relatively flat. See FIG. 10B.

GOR Modeling and Long-Term Forecast

A GOR modeling workflow was developed to capture key GOR drivers, matchavailable data and predict short- and long-term GOR trends.

The model includes the following key components:

1) A reservoir model with Bakken geological layers and reservoirproperties (FIG. 11A).

2) Hydraulic fracture representations for old and modern completiondesigns. As discussed, old completion jobs created fewer fractures witha larger fracture area per fracture, whereas modern completion jobscreated more complex fractures. The fracture properties were based onthe insights gained from relevant data collected and model calibrations.

3) Tartan gridding near the well and fractures to better characterizethe local pressure gradient and gas saturation changes (FIG. 11B).

4) PVT EOS model that was tuned to fluid sample lab data.

5) Relative permeability curves based on lab tests and productionhistory matching model calibration.

6) High quality production data, including oil/gas/water rates anddownhole measured BHP data.

The model was controlled by BHP to match oil production rates and GOR.The production history matching process was conducted in a probabilisticmanner to obtain multiple equal-probable models for uncertaintyquantification.

The old completion well matched results are given in FIG. 12A-C, wherethe early flat GOR period and intermediate term rise-and-fall patternswere successfully matched using the proposed modeling approach. Thereservoir gas saturation (S_(g)) maps at various production periods areshown in FIG. 13 to illustrate the gas saturation evolution. At thebeginning (first stage—see left-most gas saturation element), there wasno free gas in the reservoir while P_(wf)>P_(b). The second stage showsthe S_(g) map when GOR reaches the peak of the first GOR rising cycle.Small amounts of gas came out of solution and was concentrated nearfracture areas due to low reservoir matrix permeability and smalldrained rock volumes by that time. The third stage is the S_(g) map atthe end of the first build-up. Some free gas from the second stage waspushed back into reservoir by recovered pressure near fractures. Thefourth stage is the S_(g) map at a later GOR peak. The high S_(g)regions were expanded further from fractures, as compared with those inthe second stage, due to the increased cumulative production volumes,and the partially recovered BHP pressure in this period was not able tomake free gas solute back into reservoir. See the final stage (gassaturation element on the far right).

The data matched results for the modern completion well are given inFIG. 14A-C. The flat-rise-plateau GOR stages during the early andintermediate production periods were well matched.

The S_(g) and pressure evolution maps are shown in FIG. 15 . Note thatmodern completion wells' higher fracture density resulted in earlierinter-fracture production interference and larger reservoir drainagevolumes. We believe this is the main reason that the old completionwells' rise-and-fall GOR pattern and long-term slow rising trend werenot observed in the modern completion wells.

The history matched models were used to predict long-term GOR. FIG.16A-B shows the GOR prediction of old completion wells. The GORincreases at a slow pace in the long term.

For modern completion wells, two GOR scenarios were predicted based onthe pressure drawdown or well operating strategy. A more aggressivedrawdown (FIG. 17A) led to quicker GOR rise and a shorter GOR plateauperiod (FIG. 17B) before it changed to the downward trend in the longterm (FIG. 17C). Whereas a less aggressive drawdown (Error! Referencesource not found. D) slowed down GOR rise and created a prolonged GORplateau (FIG. 17E-F). Again, this shows the importance of collectinglong-term BHP data for GOR prediction.

Given the insights gained on Bakken UR well GOR trends and key drivers,some measures can be taken to mitigate rising GOR. Four potentialmethods related to completion design, development sequence and welloperation strategy are discussed below.

1) Widen fracture cluster spacing: If the rest of completion designparameters are kept the same, widening fracture cluster spacing tends tocreate larger fracture area per fracture and delay productioninterferences between fractures, which will enhance well productivityand lower GOR as illustrated in FIG. 17A-F.

2) Recharge high GOR parent wells with offset child well fracture hits:As mentioned early, fracture hits can suppress parent well GOR risingand create parent well production uplift. We can take advantage of thisunique situation in Bakken and strategically select the timing offracturing the child well as parent wells enter high GOR stages.

3) Use less aggressive drawdown: An aggressive drawdown can create sharppressure sinks near fractures or wells, given the low matrixpermeability in unconventional reservoirs. It drops the pressure inthese limited drainage areas below P_(b) faster and triggers the GORrising events. On the other hand, a less aggressive drawdown will extendthe flat GOR period and maximize the production prior to the accelerateddecline caused by rising GOR.

4) Extended well shut-in: This might be a temporary solution, but longshut-ins can lower GOR when the production is resumed thanks to thepressure build-up. However, this lowered GOR tends to be short-lived,since the flush production post shut-ins can cause more aggressivedrawdown and GOR will go back to the original rising trend within fewmonths.

In summary, we have demonstrated comprehensive analysis and modelingstudies on Bakken UR well GOR providing the benefit of forecasting,improved design, completion trends, and correlations between GOR andBHP. Forecasting GOR and gas rates are crucial to development plans,offtake strategy, facility design and flaring reduction. The Bakkenfield has seen a large increase in GOR and gas rates over the lastseveral years driven by completion design, depletion, operationalstrategy, and fluid PVT properties. Old sliding sleeve completion wellGOR shows cyclical rise-and-fall patterns with a gradually increasinglong-term trend, whereas modern completion wells show rising GOR trendafter their BHPs drop below P_(b) and then reach an intermediate-termplateau.

Strong correlations between GOR and BHP pressure were observed. Downholegauge BHP pressure is critical data for GOR behavior analysis andlong-term forecast. No strong critical gas saturation behavior wasobserved from Bakken wells. GOR can be used a diagnostic tool to monitorreservoir depletion and drainage. A focused GOR modeling approach can becrucial in the forecasting. Several measures can be taken to mitigatethe high GOR, while ultimately improving well economics.

Hardware & Software

The present disclosure also relates to a computing apparatus forperforming the operations described herein. This apparatus may bespecially constructed for the required purposes of modeling, or it maycomprise a general-purpose computer selectively activated orreconfigured by a spreadsheet program and reservoir simulation computerprogram stored in the computer. Such computer programs may be stored ina computer readable storage medium, preferably non-transitory, such as,but is not limited to, any type of disk including floppy disks, opticaldisks, CD-ROMs, and magnetic-optical disks, read-only memories (ROMs),random access memories (RAMs), EPROMs, EEPROMs, magnetic or opticalcards, or any type of media suitable for storing electronicinstructions, each coupled to a computer system bus.

In one embodiment, the computer system or apparatus may includegraphical user interface (GUI) components such as a graphics display anda keyboard, which can include a pointing device (e.g., a mouse,trackball, or the like, not shown) to enable interactive operation. TheGUI components may be used both to display data and processed data andto allow the user to select among options for implementing aspects ofthe method or for adding information about reservoir inputs orparameters to the computer programs. The computer system may store theresults of the system and methods described above on disk storage, forlater use and further interpretation and analysis. Additionally, thecomputer system may include on or more processors for running saidspreadsheet and simulation programs.

Hardware for implementing the inventive methods may preferably includemassively parallel and distributed Linux clusters, which utilize bothCPU and GPU architectures. Alternatively, the hardware may use a LINUXOS, XML universal interface run with supercomputing facilities providedby Linux Networx, including the next-generation Clusterworx Advancedcluster management system.

Another system is the Microsoft Windows 7 Enterprise or Ultimate Edition(64-bit, SP1) with Dual quad-core or hex-core processor, 64 GB RAM withFast rotational speed hard disk (10,000-15,000 rpm) or solid state drive(300 GB) with NVIDIA Quadro K5000 graphics card and multiple highresolution monitors. Of course, such systems may be updated with time,as computer hardware continues to improve at great rates.

Slower systems could also be used because the processing is lesscomputation intensive than for example, 3D seismic processing.

Reservoir simulation programs can be any known in the art, possiblymodified for use herein, or any novel purpose-built system. Existingcommercial packages include MEERA, ECLIPSE, RESERVOIR GRAIL, 6X, VOXLER,SURFER, the CMG suite, LANDMARK NEXUS, and the like. Open sourcepackages include BOAST—Black Oil Applied Simulation Tool, MRST—theMATLAB Reservoir Simulation Toolbox and OPM—The Open Porous Media (OPM).

The following references are each incorporated by reference in itsentirety for all purposes:

Carlson, C. G.; Anderson, S. B.; Sedimentary and tectonic history ofNorth Dakota part of Williston Basin. AAPG Bulletin; 49 (11): 1833-1846.doi.org/10.1306/A663386C-16C0-11D7-8645000102C1865D.

Cipolla, C.; Litvak, M.; Prasad, R. S.; McClure, M. “Case history ofdrainage mapping and effective fracture length in the Bakken.” Paperpresented at the SPE Hydraulic Fracturing Technology Conference andExhibition, The Woodlands, Tex., USA, February 2020.doi.org/10.2118/199716-MS

Carlsen, M. L.; Whitson, C. H.; Alavian, A.; Martinsen, S. Ø.; Mydland,S.; Singh, K.; Younus, B.; Yusra, I. “Fluid Sampling in TightUnconventionals.” Paper presented at the SPE Annual Technical Conferenceand Exhibition, Calgary, Alberta, Canada, September 2019.doi.org/10.2118/196056-MS

Gaswirth, S. B.; Marra, K. R.; Cook, T. A.; Charpentier, R. R.; Gautier,D. L.; Higley, D. K.; Klett, T. R.; Lewan, M. D.; Lillis, P. G.; Schenk,C. J.; Tennyson, M. E.; Whidden, K. J. “Assessment of undiscovered oilresources in the Bakken and Three Forks Formations, Williston BasinProvince, Montana, North Dakota, and South Dakota, 2013” USGS NationalAssessment of Oil and Gas Sheet 2013-2013, p. 4.

Jones, R. S. “Producing-Gas/Oil-Ratio behavior of multifracturedhorizontal wells in tight oil reservoirs.” SPE Res Eval & Eng 20 (2017):589-601. doi.org/10.2118/184397-PA

Lei, G.; Cheng, N. “Liquid-rich shale versus conventional depletionperformance.” Paper presented at the SPE/EAGE European UnconventionalResources Conference and Exhibition, Vienna, Austria, February 2014.doi.org/10.2118/167788-MS

Liu, Y.; Bordoloi, S.; McMahan, N.; Zhang, J.; Rajappa, B.; Long, H.;Michael, E. “Bakken infill pilot analysis and modeling: Characterizingunconventional reservoir potentials.” Paper presented at theSPE/AAPG/SEG Unconventional Resources Technology Conference, Virtual,July 2020. doi.org/10.15530/urtec-2020-2177

Luo, S.; Lutkenhaus, J.; Nasrabadi, H. “A framework for incorporatingNanopores in compositional simulation to model the unusually high GORobserved in shale reservoirs.” Paper presented at the SPE ReservoirSimulation Conference, Galveston, Tex., USA, April 2019.doi.org/10.2118/193884-MS

Pradhan, Y. “Observed gas-oil ratio trends in liquids rich shalereservoirs.” Paper presented at the SPE/AAPG/SEG UnconventionalResources Technology Conference, Virtual, July 2020.doi.org/10.15530/urtec-2020-3229

Raterman, K.; Liu, Y.; Warren, L. “Analysis of a drained rock volume: AnEagle Ford example.” Paper presented at the SPE/AAPG/SEG UnconventionalResources Technology Conference, Denver, Colo., USA, July 2019.doi.org/10.15530/urtec-2019-263

Raterman, K.; Liu, Y.; Roy, B.; Friehauf, K.; Thompson, B.; Janssen, A.“Analysis of a multi-well Eagle Ford pilot.” Paper presented at theSPE/AAPG/SEG Unconventional Resources Technology Conference, Virtual,July 2020. doi.org/10.15530/urtec-2020-2570

Whitson, C. H.; Sunjerga, S. “PVT in liquid-rich shale reservoirs.”Paper presented at the SPE Annual Technical Conference and Exhibition,San Antonio, Tex., USA, October 2012. doi.org/10.2118/155499-MS

ASTM D1298 “Standard test method for density, relative density or APIgravity of crude petroleum and liquid petroleum products by hydrometermethod.”

ASTM D4052 “Standard test method for density, relative density and APIgravity of liquids by digital density meter.”

What is claimed: 1) A method of optimizing oil production from one ormore well(s) in a reservoir, said method comprising: a) providing amodel of one or more well(s) in a reservoir; b) inputting well data intosaid model, said well data selected from geological layers, reservoirproperties, fracturing data, completion data, permeability data,geochemistry, and combinations thereof; c) inputting historicalproduction data from said one or more well(s) into said model, saidhistorical data selected from PVT data, BHP, oil production rates, gasproduction rates, water production rates, and combinations thereof; d)controlling said model to match one or more parameters selected fromproduction rates, gas to oil ratio (GOR), bottom hole pressure (BHP),cumulative oil production (COP), and combinations thereof, in aprobabilistic manner to obtain a plurality of historical models; e)verifying one or more test models against said plurality of historicalmodels to identify an optimal model with minimum error; f) using saidoptimal model to predict one or more parameters selected from productionrates, gas to oil ratio (GOR), bottom hole pressure (BHP), cumulativeoil production (COP), and combinations thereof from said well into afuture; g) optimizing a production plan using said predicted parameters;h) implementing said optimized production plan in said well, whereby oilproduction is optimized as compared to a similar well produced withoutsaid optimized production plan. 2) The method of claim 1, wherein saidreservoir is an unconventional reservoir. 3) The method of claim 1,wherein said reservoir is a hybrid shale and limestone reservoir. 4) Themethod of claim 1, wherein said model in a) has finer gridding near saidone or more well(s). 5) The method of claim 4, wherein said finergridding is Tartan gridding. 6) The method of claim 1, wherein saidoptimized reservoir plan includes reduced drawdown to reduce GOR. 7) Themethod of claim 1, wherein said optimized reservoir plan includeswidening fracture cluster spacing to reduce GOR. 8) The method of claim1, wherein said optimized reservoir plan includes recharging high GORparent wells with offset child well fracture hits to reduce GOR. 9) Themethod of claim 1, wherein said optimized reservoir plan includesextending well shut-in time to reduce GOR. 10) A method of reducing GORin oil production from one or more well (s) in a reservoir, said methodcomprising: a) providing a model of one or more well(s); b) inputtingwell data into said model, said well data selected from geologicallayers, reservoir properties, fracturing data, completion data,permeability data, geochemistry, and combinations thereof; c) inputtinghistorical production data from said one or more well(s) into saidmodel, said historical data selected from PVT data, BHP, oil productionrates, gas production rates, water production rates, and combinationsthereof; d) controlling said model to match one or more parametersselected from production rates, gas to oil ratio (GOR), bottom holepressure (BHP), cumulative oil production (COP), or combinations thereofin a probabilistic manner to obtain a plurality of historical models; e)verifying one or more test models against said historical models toidentify an optimal model with minimum error; f) using said optimalmodel to predict gas to oil ratio (GOR) from said one or more well(s)into a future; g) optimizing a production plan using said predicted GORto reduce gas production; h) implementing said optimized production planin said reservoir, whereby GOR is reduced as compared to said predictedGOR. 11) The method of claim 10, wherein said reservoir is anunconventional reservoir. 12) The method of claim 10, wherein saidreservoir is a hybrid shale and limestone reservoir. 13) The method ofclaim 10, wherein said model in a) has finer gridding near said well.14) The method of claim 13, wherein said finer gridding is Tartangridding. 15) The method of claim 10, wherein said optimized reservoirplan includes reduced drawdown to reduce GOR. 16) The method of claim10, wherein said optimized reservoir plan includes widening fracturecluster spacing to reduce GOR. 17) The method of claim 10, wherein saidoptimized reservoir plan includes recharging high GOR parent wells withoffset child well fracture hits to reduce GOR. 18) The method of claim10, wherein said optimized reservoir plan includes extending wellshut-in to reduce GOR. 19) The method of claim 10, wherein saidoptimized reservoir plan includes one or more of: a) reduced drawdown toreduce GOR; b) widening fracture cluster spacing to reduce GOR; c)recharging high GOR parent wells with offset child well fracture hits toreduce GOR; d) extending well shut-in to reduce GOR;